when you log out of the container, so don't edit the other files!
All needed dependencies are already installed in this container
-(SimGrid, the C/C++/Fortran compilers, make, pajeng and R). Vite being
+(SimGrid, the C/C++/Fortran compilers, make, pajeng, R and pajengr). Vite being
only optional in this tutorial, it is not installed to reduce the
image size.
sudo apt install simgrid pajeng make gcc g++ gfortran vite
+For R analysis of the produced traces, you may want to install R,
+and the `pajengr<https://github.com/schnorr/pajengr#installation/>_ package.
+
+.. code-block:: shell
+
+ sudo apt install r-base r-cran-devtools cmake flex bison
+ Rscript -e "library(devtools); install_github('schnorr/pajengr');"
+
To take this tutorial, you will also need the platform files from the
previous section as well as the source code of the NAS Parallel
Benchmarks. Just clone `this repository
.. code-block:: shell
smpirun -np 4 -platform ../cluster_backbone.xml -trace --cfg=tracing/filename:lu.S.4.trace bin/lu.S.4
- pj_dump --ignore-incomplete-links lu.S.4.trace | grep State > lu.S.4.state.csv
You can then produce a Gantt Chart with the following R chunk. You can
either copy/paste it in a R session, or `turn it into a Rscript executable
.. code-block:: R
+ library(pajengr)
library(ggplot2)
# Read the data
- df_state = read.csv("lu.S.4.state.csv", header=F, strip.white=T)
+ df_state = pajeng_read("lu.S.4.trace")
names(df_state) = c("Type", "Rank", "Container", "Start", "End", "Duration", "Level", "State");
df_state = df_state[!(names(df_state) %in% c("Type","Container","Level"))]
df_state$Rank = as.numeric(gsub("rank-","",df_state$Rank))
